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Related Concept Videos

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z scores are the standardized values obtained after converting a normal distribution into a standard normal distribution. A z score is measured in units of the standard deviation. The z score tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a z score of...
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Compartment Models: Single-Compartment Model01:14

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The single-compartment model serves as a simplified representation of the human body. This model assumes that the body functions as a single, well-mixed open compartment. When a drug is administered intravenously, it enters the body and quickly distributes uniformly. The drug then undergoes biotransformation and elimination, ultimately leaving the body. The volume of this compartment is referred to as the apparent volume of distribution into which the drug can uniformly distribute. In this...
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The homogenate obtained after cell lysis contains various membrane-bound organelles that can be further separated into pure fractions by subcellular fractionation. These isolates are used to study specific cellular components, analyze localized protein activity, and are even employed in diagnostics. Fractionation is typically achieved using centrifugation methods, the most common being density-gradient and differential centrifugation.
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The two-compartment model divides the body into central and peripheral compartments to account for varying blood perfusion rates among organs and tissues, affecting drug distribution. The central compartment includes blood and highly perfused tissues with rapid drug distribution, while the peripheral compartment contains tissues with slower drug distribution. After a single IV bolus dose, the drug concentration is high in plasma and low in tissues. The drug distribution between compartments...
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This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
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Related Experiment Video

Updated: Jul 30, 2025

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces
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CscoreTool-M infers 3D sub-compartment probabilities within cell population.

Xiaobin Zheng1, Joseph R Tran1, Yixian Zheng1

  • 1Department of Embryology, Carnegie Institution for Science, Baltimore, MD 21218, United States.

Bioinformatics (Oxford, England)
|May 11, 2023
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Summary

CscoreTool-M infers multiple 3D genome sub-compartments from Hi-C data, improving accuracy and quantifying cell population heterogeneity. The tool reveals cell cycle-specific genome organization and functional gene enrichment in sub-compartments.

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Area of Science:

  • Genomics and computational biology
  • Molecular and cell biology
  • Epigenetics and chromatin structure

Background:

  • Three-dimensional (3D) genome organization is crucial for cellular function and is studied using Hi-C sequencing.
  • Existing computational methods struggle to account for cell population heterogeneity in 3D genome organization analysis.
  • Understanding sub-compartment dynamics is key to deciphering complex genomic regulation.

Purpose of the Study:

  • To introduce CscoreTool-M, a novel probabilistic modeling approach for inferring multiple 3D genome sub-compartments from Hi-C data.
  • To address the limitations of current methods in handling cell population heterogeneity.
  • To provide a tool for accurate sub-compartment identification and quantification of genomic heterogeneity.

Main Methods:

  • Development of CscoreTool-M, a probabilistic modeling tool for Hi-C data analysis.
  • Inference of compartment scores representing the probability of genomic regions within specific sub-compartments.
  • Comparative analysis of CscoreTool-M against existing methods for accuracy in sub-compartment identification.

Main Results:

  • CscoreTool-M accurately infers active and repressed chromatin sub-compartments, outperforming existing methods.
  • The tool quantifies sub-compartment localization heterogeneity within cell populations.
  • Analysis revealed higher heterogeneity in proliferating cells, linked to cell cycle stages, and identified potential early-G1 chromatin regions near the nuclear lamina.
  • CscoreTool-M identified sub-compartments enriched for housekeeping and cell-type-specific genes.

Conclusions:

  • CscoreTool-M offers a significant advancement in analyzing 3D genome organization from Hi-C data, particularly for heterogeneous cell populations.
  • The method accurately deconvolves cell cycle-specific genome organization and identifies functionally relevant chromatin sub-compartments.
  • CscoreTool-M provides a valuable tool for researchers studying chromatin dynamics, gene regulation, and cell-type specificity.